code: def __init__(
      self,
      path=".",
      subset_pct=100,
      normalize=True,
      contrast_normalize=False,
      whiten=False,
      pad_classes=False,
      batch_size=128,
  ):
      super(DUMMY, self).__init__(
          "dummy", "dummy", 1, path=path, subset_pct=subset_pct
      )
      self.batch_size = batch_size
      pass
  
imports: from __future__ import division
  from future import standard_library
  from builtins import str
  import gzip
  import logging
  import numpy
  import os
  import tarfile
  from neon.util.compat import pickle
  from neon.util.compat import pickle_load
  from neon.data.datasets import Dataset
  from neon.data.dataiterator import ArrayIterator
label_desc: Use image node_id 1 to create a new DUMMY object from inherited base classes: Dataset with example: obj = DUMMY(path, subset_pct, normalize, contrast_normalize, whiten, pad_classes, batch_size)